-------- Forwarded Message -------- Subject: [AISWorld] CFP: Special issue on AI Fairness, Trust and Ethics Date: Mon, 1 Jul 2019 05:44:15 -0400 From: Lionel Robert lprobert@umich.edu To: Lionel Robert lprobert@umich.edu
*AIS Transactions on HCI (THCI) https://aisel.aisnet.org/thci/* *Special issue on AI Fairness, Trust and Ethics*
*Special Issue Editors:* Lionel P. Robert Jr., University of Michigan Gaurav Bansal, University of Wisconsin-Green Bay Nigel Melville, University of Michigan Tom Stafford, Louisiana Tech University
*Submission Deadline: Full papers due February 15, 2020* AI is rapidly changing every aspect of our society from how we conduct business, socialize and exercise. AI has amplified our productivity as well as biases. John Giannandrea, who leads AI at Google, recently lamented in the MIT Technology Review that the dangers posed by the ability of AI systems to learn human prejudices were far greater than those posed by killer-robots. This phenomenon is problematic because AI systems are making millions of decisions every minute many of which are invisible to the users and incomprehensible to the designers. Their opaqueness is a significant cause of worry and leaves many unanswered questions.
Fairness, Trust and Ethics are at the core of many of the issues underlying the implications of AI. Fairness is undermined when managers rely blindly on “objective” AI outputs to “augment” or replace their decision making. Managers often ignore the limitations of their assumptions and the relevance of the data that was used to train and test AI models, resulting in bias decisions that are hard to detect or appeal. Trust is undercut, when AI is used to render false or misleading images of individuals saying or doing things that are simply not true. These false images are making it difficult for society to trust what they see or hear. Ethical challenges are presented when decisions used by AI lead to further inequalities in the society. Examples include: displaced workers and shortages of affordable housing due to rental apartments and housing units being diverted to higher paying Airbnb short term vacationers.
Despite the potential transformative effects, research on AI in the Information Systems field is still scarce, and as a result, our knowledge on the impacts of AI are still far from conclusive. Yet, it is very important from the business and technical perspective that we research and examine issues of fairness, trust and ethics with AI. This examination is critical as issues of fairness, trust and ethics lie at the heart of addressing the new challenges facing the development and use of AI throughout our society. This is especially true, as there has been a rapid increase in the number of applications of AI in an ever increasing number of new areas. In all, AI has the potential to disrupt and dramatically change the interactions between humans and technologies.
This Special Issue on AI Fairness, Trust and Ethics calls for research that can unpack the potential, challenges, impacts, and theoretical implications of AI. We welcome research from different perspectives regardless of the approach or methodology. Submissions with novel theoretical implications that span disciplines are strongly encouraged. We seek submissions that can improve our understanding about the impacts of AI in organizations and our broader society.
*Potential topics include (but are not limited to):*
- Defining fair, ethical and trustworthy AI - Antecedents and consequents for fair, ethical and trustworthy AI - Designing, implementing and deploying fair, ethical and trustworthy AI - Theories of fair, ethical and trustworthy AI - Policy and governance for fair, ethical and trustworthy AI - Appropriate and inappropriate applications of AI - Legal responsibilities for decisions made by AI - AI biases - AI algorithm transparency – how to improve - The dark side of AI - AI equality vs AI equity - Implications of unfair, unethical and untrustworthy AI
*Key Dates:* Optional one page abstract submissions: Oct 1, 2019 Selected abstracts invited for poster presentations at Pre-ICIS 2019 SIGHCI workshop on Dec 15, 2019 First round submissions: Feb 15, 2020 First round decisions: April 15, 2020 Second round submissions: July 15, 2020 Second round decisions to authors: Sep 15, 2020 Third and final round submissions: November 1, 2020 Final decisions to authors: November 15, 2020 Targeted publication date: December 31, 2020
To submit a manuscript, read the "Information for Authors" and "THCI Policy" pages, then go to http://mc.manuscriptcentral.com/thci.
*Contact:* All questions about submissions should be emailed to: *AIS-THCI-AI-FTE-SI-requests@umich.edu AIS-THCI-AI-FTE-SI-requests@umich.edu.*
Linke to: *Call For Papers: Special issue on AI Fairness, Trust and Ethics https://bit.ly/2JcrDT7*
Best regards,
Lionel
*New Paper(s):* Du, N., Haspiel, J., Zhang, Q., Tilbury, D., Pradhan, A., Yang, X. J. and *Robert, L. P. *(Accepted 2019). *Look Who’s Talking Now: Implications of AV’s Explanations on Driver’s Trust, AV Preference, Anxiety and Mental Workload*, *Transportation Research Part C: Emerging Technologies*, (pdf http://hdl.handle.net/2027.42/149154), forthcoming, link to the article provided by the author: http://hdl.handle.net/2027.42/149154 and http://arxiv.org/abs/1905.08878.
*Robert, L. P. *(2019*)*. *Are Automated Vehicles Safer than Manually Driven Cars?*, *AI & Society*, (pdf https://deepblue.lib.umich.edu/bitstream/handle/2027.42/149146/AI%26S%20Are%20Automated%20Vehicles%20Safe%20Final%20Version.pdf?sequence=1&isAllowed=y ), link to publisher's site: https://doi.org/10.1007/s00146-019-00894-y copy provided by the author: http://hdl.handle.net/2027.42/149146.
*Robert, L. P.* ( 2019). *The Future of Pedestrian-Automated Vehicle Interactions*, *XRDS: Crossroads*, 25(3), pp. 30-33. (pdf https://deepblue.lib.umich.edu/bitstream/handle/2027.42/148533/Robert%202019.pdf?sequence=1&isAllowed=y ), DOI: https://doi.org/10.1145/3313115 article provided by author: http://hdl.handle.net/2027.42/148533 or http://arxiv.org/abs/1904.06417 or http://ssrn.com/abstract=3370618.
Petersen, L., *Robert, L.P.*, Yang, X. J. Tilbury, D. (2019). *Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance*, *SAE International Journal of Connected and Automated Vehicles*, 2(2), (pdf https://deepblue.lib.umich.edu/bitstream/handle/2027.42/148141/SA%20Trust%20-%20SAE-%20Public.pdf?sequence=1&isAllowed=y), DOI:10.4271/12-02-02-0009 link to the article https://saemobilus.sae.org/content/12-02-02-0009/ and copy provided by the author: http://hdl.handle.net/2027.42/148141 and http://arxiv.org/abs/1903.05251.
Lionel P. Robert Jr. Associate Professor, School of Information https://www.si.umich.edu/people/lionel-robert Core Faculty, Michigan Robotics Institute https://robotics.umich.edu/core-faculty/ Affiliate Faculty, National Center for Institutional Diversity https://lsa.umich.edu/ncid Affiliate Faculty, Michigan Interactive and Social Computing http://misc.si.umich.edu/ Director of MAVRIC https://mavric.si.umich.edu Co-Director of DOW Lab University of Michigan Email: lprobert@umich.edu UMSI Website https://www.si.umich.edu/directory/lionel-robert | Personal Website https://sites.google.com/a/umich.edu/lionelrobert/home MAVRIC: https://mavric.si.umich.edu _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org